(a) Field
The present invention relates to a method for prognosing or predicting overall survival (OS) or metastasis in a subject with triple negative (TN) breast cancer. More specifically, the invention relates to two sets of biomarkers, one set useful for prognosing or predicting OS in a subject with TN breast cancer and the other useful for prognosing or predicting metastasis in a subject with TN breast cancer.
(b) Related Prior Art
Tumor-associated antigens (TAAs) can help diagnose various tumors and sometimes determine the response to therapy or recurrence. An ideal tumor marker would be released only from tumor tissue, be specific for a given tumor type, be detectable at low levels of tumor cell burden, have a direct relationship to the tumor cell burden, and be present in all subjects with the tumor. However, although most tumors release detectable antigenic macromolecules into the circulation, no tumor marker has all the requisite characteristics to provide enough specificity or sensitivity to be used in early diagnosis or mass cancer screening programs.
Proteomic analyses of early stages cancers represent a new diagnostic tool for early detection of the disease. This technique evaluates the presence of various biomarkers in readily accessible body fluids such as serum, urine or saliva that are particular of specific changes in gene expression only occurring in cancer cells. Protein-based assays, such as the ELISA system, are used to evaluate the presence of biomarkers, therefore allowing detection and monitoring of cancer. The search for always more reliable cancer-related biomarkers is oriented towards proteins that are overexpressed, as a consequence of the disease process, and subsequently shed into body fluid. Novel proteomics methods and technologies are being used to discover new biomarkers for early-stage disease. Those methods comprise, besides the ELISA system, other antibody arrays, protein-based microarray technologies and multiplexed on-chip technologies. Despite their utility, there are several inherent disadvantages to these methods, such as the fact that they are often limited by the requirements for highly specific, high-affinity antibodies, two-site approaches and/or sensitive detection and signal amplification systems. Moreover, the development of proteomic pattern diagnostics is intricate since the specificity between physiologic biomarkers and the various types of cancer is hard to establish.
Breast cancer is the second most common cause of cancer-related mortality in Western women. One of the important challenges in current breast cancer research is to develop effective methods to determine whether a patient is likely to have a recurrence or progress to the aggressive, metastatic disease in order to aid clinicians in deciding the appropriate course of treatment. This is especially true for women with so called triple negative (TN) breast cancer. These tumors can be identified by the fact that they do not express the estrogen or progesterone receptors and express only normal (not amplified) levels of the human epidermal growth factor receptor 2 (HER2). However, it is currently impossible to predict the outcome of TN patients based solely on the pathological evaluation of the tumor.
Accordingly, novel methods of prognosis or classifying breast cancer subtypes are highly desirable.